Missing Observations and Data Quality Improvement
作者： Carlos N. Bouza-Herrera
DOI: 10.1007/978-3-642-39899-5_1
关键词:
摘要: Missing data is a well-recognized problem which arises in statistical inferences and analysis. We address different possible ways to handle missing data, ameliorate its effect on the reliability accuracy of survey-based inferences. Subsampling non-respondents imputation values, are considered as methods for dealing with non-responses. This book presents work developed Ranked Set Sampling (RSS) data. RSS relatively new sampling design. chapter may be an introduction rest oeuvre.
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